Field of the Invention
The present invention relates to an image processing apparatus and image processing method for performing a quantization process to form an image on a print medium.
Description of the Related Art
When using a pseudo gradation method to print an image, it is necessary to quantize multi-valued image data, and as a quantization method used for the quantization, an error diffusion method and a dither method are known. In particular, the dither method that compares a preliminarily stored threshold value and a gradation value of multi-valued data with each other to determine dot printing or non-printing has a small processing load as compared with the error diffusion method, and is therefore widely used in many image processing apparatuses. In the case of such a dither method, in particular, dot dispersibility in a low gradation range becomes problematic; however, for example, U.S. Pat. No. 5,111,310 proposes a method adapted to use a threshold value matrix having blue noise characteristics as a threshold value matrix for obtaining preferable dot dispersibility.
FIGS. 18A to 18C are diagrams for explaining a dither process using a threshold value matrix having blue noise characteristics. FIG. 18A illustrates an example of image data to be inputted into a 10-pixel×10-pixel area. This example shows a state where a gradation value of “36” is inputted to all the pixels. FIG. 18B illustrates a threshold value matrix prepared corresponding to the above 10-pixel×10-pixel area. Each of the pixels is related to any of threshold values of 0 to 254. In the dither method, when a gradation value indicated by multivalued image data is larger than a threshold value, a corresponding pixel is designated as dot printing “1”. On the other hand, when a gradation value indicated by multivalued image data is equal to or less than a threshold value, a corresponding pixel is designated as dot non-printing “0”. FIG. 18C illustrates a quantization result based on the dither method. Pixels representing printing “1” are indicated in gray, and pixels representing non-printing “0” are indicated in white. The distribution of printing “1” pixels as seen in FIG. 18C depends on threshold value arrangement in a threshold value matrix. By using the threshold value matrix having blue noise characteristics as in FIG. 18B, even in the case where the same pieces of multivalued data are inputted into the predetermined area as in FIG. 18A, the printing “1” pixels are arranged in a high dispersibility state as in FIG. 18C.
FIGS. 19A and 19B are diagrams illustrating blue noise characteristics and human visual characteristics or a human transfer function (VTF) at a visibility distance of 300 mm. In both of the diagrams, the horizontal axis represents a frequency (cycles/mm), indicating lower and higher frequencies toward the left and right of the graph, respectively. On the other hand, the vertical axis represents intensity (power) corresponding to each frequency.
Referring to FIG. 19A, the blue noise characteristics are characterized by, for example, a suppressed low frequency component, a rapid rise, and a flat high frequency component. A frequency fg corresponding to a peak resulting from the rapid rise is referred to as a principal frequency. On the other hand, for the human visual characteristics (VTF) illustrated in FIG. 19B, as an example, the following Dooley approximate expression is used. In the expression, l represents an observation distance and f represents a frequency.VTF=5.05×exp(−0.138×πlf/180)×(1−exp(0.1×πlf/180))  Expression 1
As can be seen from FIG. 19B, the human visual characteristics have high sensitivity in a lower frequency range, but sensitivity in a higher frequency range is low. That is, a lower frequency component is conspicuous, whereas a higher frequency component is inconspicuous. The blue noise characteristics are based on such visual characteristics, and adapted to, in the visual characteristics, hardly have power in the highly sensitive (conspicuous) lower frequency range, but have power in the low sensitive (inconspicuous) higher frequency range. For this reason, when a person visually observes an image subjected to a quantization process using a threshold value matrix having blue noise characteristics, dot deviation or periodicity is unlikely to be perceived, and the image is recognized as a comfortable image.
On the other hand, U.S. Pat. No. 6,867,884 discloses a dither method for solving a situation where even though preferable dispersibility can be obtained on a color material basis (i.e., on a color basis), when printing an image using multiple color materials (i.e., mixed color), dispersibility is deteriorated to make graininess conspicuous. Specifically, U.S. Pat. No. 6,867,884 discloses a method that prepares one common dither matrix having preferable dispersibility as in FIG. 18B, and performs a quantization process while shifting mutual threshold values among multiple colors. The quantization method disclosed in U.S. Pat. No. 6,867,884 is herein referred to a color correlating process. The color correlating process makes it possible to achieve preferable image quality even in a mixed color image because dots having different colors are mutually exclusively printed in a highly dispersive state in a low gradation range.
However, the above-described color correlating process can make graininess inconspicuous in a dot pattern in which ink dots of multiple colors are mixed, but may make the dispersibility of dots of a specific ink rather conspicuous. U.S. Pat. No. 6,867,884 gives priority to enhancing the dispersibility of a black ink having the strongest dot power among multiple color inks, and sets black for a channel for which a threshold value is set without offsetting among multiple channels using the common threshold value matrix. However, for example, when expressing a full color image using cyan, magenta, and yellow without using black, if a channel for the lowest threshold value range is set for one of cyan and magenta having equivalent dot power, the graininess of the other one may become conspicuous. A specific description will be given below.
FIG. 20 is a diagram illustrating a dot print state obtained when performing the color correlating process with inks of three colors assigned to first to third channels. While using the same threshold value matrix having blue noise characteristics, a threshold value is set for data of the first color assigned to the first channel without offsetting, and a threshold value offset on the basis of the data of the first color is set for data of the second color. Further, for data of the third color, a threshold value offset on the basis of the pieces of data of the first and second colors is set. For this reason, in a dot pattern 1910 of the first color, and in the sum 1940 of dot patterns of the first to third colors, dots are preferably dispersed and graininess is also suppressed. On the other hand, in each of the dot pattern 1920 of the second color and the dot pattern 1930 of the third color, both dispersibility and graininess are deteriorated.
FIGS. 21A to 21C are diagrams quantitatively illustrating the graininesses of the dot patterns illustrated in FIG. 20. In FIG. 21A, the horizontal axis represents a spatial frequency, and the vertical axis represents average intensity (power) corresponding to the spatial frequency. It turns out that each of the dot patterns of the first color and the mixed color has sufficiently suppressed power in a lower frequency range and also has a power peak positioned near a principal frequency fg. That is, each of the dot patterns of the first color and the mixed color has blue noise characteristics. On the other hand, each of the dot patterns of the second and third colors has a certain level of power in the lower frequency range, does not have a steep peak, and has power already reduced near the principal frequency fg. That is, each of the dot patterns of the second and third colors does not have blue noise characteristics.
FIG. 21B is a diagram illustrating, as response values, results of multiplying the frequency characteristics illustrated in FIG. 21A by the human visual characteristics (VTF) illustrated in FIG. 18B. Also, FIG. 21C illustrates integrated values of the response values in FIG. 21B. A larger response value or a larger response integrated value means that the graininess of a dot pattern is more easily visually perceived. In this example, the response or integrated values of the second and third color dot patterns are larger than those of the first and mixed color dot patterns, and therefore the graininesses of the second and third color dot patterns are easily perceived. That is, even when employing the method disclosed in U.S. Pat. No. 6,867,884 to suppress graininess in a mixed color image, the graininess of a dot pattern of a specific ink color may be conspicuous in the mixed color image to deteriorate image quality.